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Edward Adelson. Li, Rui, Ph. D. Massachusetts Institute of Technology Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2015-11-09T19:51:54Z 2015-11-09T19:51:54Z 2015 2015 http://hdl.handle.net/1721.1/99834 927405739 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 87-95). For robots to perform advanced manipulation in a world of unknowns, touch is a critical source of information, and a high-quality tactile sensor is essential. However, existing tactile sensors generally are low-resolution and/or non-compliant, making it difficult to capture detailed contact information for manipulation that humans are very good at. GelSight was first developed a few years ago to capture micro-scale surface topography and converts pressure patterns to images, making it promising for high-quality tactile sensing. However, the original devices were big, relatively slow, and expensive for robotic applications. In this work, we developed a new tactile sensor based on GelSight, which we call fingertip GelSight sensor, that is much more compact, faster and less expensive. Despite that, the fingertip sensor has high resolution, on the order of tens of microns, high compliance and high sensitivity. We demonstrated its unparalleled capabilities as a new-generation robotic fingertip for manipulation, in terms of localization and manipulation of small parts, normal and shear force estimation, and slip detection, as well as for material recognition, in terms of 3D surface texture classification. With image processing and machine learning techniques applied on the tactile images obtained, the fingertip GelSight sensor opens many possibilities for robotic manipulation that would otherwise be difficult to perform. by Rui Li. Ph.D. 95 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Touching is believing : sensing and analyzing touch information with GelSight Sensing and analyzing touch information with GelSight Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="10f79717-d342-4c16-ad66-eb8f702b98eb"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Touching is believing : sensing and analyzing touch information with GelSight</Title> <Subtitle>Sensing and analyzing touch information with GelSight</Subtitle> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2015</PublicationDate> <Authors> <Author> <DisplayName>Li, Rui, Ph. D. Massachusetts Institute of Technology</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>For robots to perform advanced manipulation in a world of unknowns, touch is a critical source of information, and a high-quality tactile sensor is essential. However, existing tactile sensors generally are low-resolution and/or non-compliant, making it difficult to capture detailed contact information for manipulation that humans are very good at. GelSight was first developed a few years ago to capture micro-scale surface topography and converts pressure patterns to images, making it promising for high-quality tactile sensing. However, the original devices were big, relatively slow, and expensive for robotic applications. In this work, we developed a new tactile sensor based on GelSight, which we call fingertip GelSight sensor, that is much more compact, faster and less expensive. Despite that, the fingertip sensor has high resolution, on the order of tens of microns, high compliance and high sensitivity. We demonstrated its unparalleled capabilities as a new-generation robotic fingertip for manipulation, in terms of localization and manipulation of small parts, normal and shear force estimation, and slip detection, as well as for material recognition, in terms of 3D surface texture classification. With image processing and machine learning techniques applied on the tactile images obtained, the fingertip GelSight sensor opens many possibilities for robotic manipulation that would otherwise be difficult to perform.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>